JP2020509500A - Control method of autonomous mobile robot - Google Patents

Abstract

An object of the present invention is to make the operation of an autonomous mobile robot, particularly, the operation of a blocking area simple and robust. A method for controlling an autonomous mobile robot configured to independently navigate in a robot use area using a sensor and a map, wherein an obstacle is detected based on measurement data obtained from the sensor. Detecting and determining the position of the detected obstacle; and controlling the robot to avoid collision with the detected obstacle, wherein the map comprises at least one virtual obstruction. A method comprising the step of displaying map data in which an area is indicated, wherein said at least one virtual occlusion area is taken into account in the control of the robot in the same way as to an actually detected obstacle. [Selection diagram] FIG.

Description

  This specification relates to the field of autonomous mobile robots, and more particularly to the safe operation of autonomous mobile service robots.

  In recent years, autonomous mobile robots, especially service robots, have been increasingly used in personal homes. Possible applications include, for example, a cleaning robot that cleans and / or wipes the floor, or a surveillance robot that detects potential dangers such as intruders and fires during patrols.

  The requirement that the user needs is, for example, that the robot has reached all the important points of the used area and does its job. For certain applications, it may be advantageous to block individual areas of the robot. For example, it may be desirable for a robot to avoid a children's playground because many small objects can hinder or be damaged by the robot.

US Patent Application Publication US 2014316636 European Patent Application Publication EP 3079030 German patent application DE 102015006014

  The known solution allows the user to mark the area of use of the robot. The robot can detect it with a sensor, and the mark indicates the blocking area to the robot. One example is a kind of "lighthouse" that emits infrared signals. However, this solution relies on its own power source (eg, a battery), which may limit reliability. In addition, infrared signals must be accurately aligned, which limits their range. Another example is a magnetic tape that can be detected by a robot. The magnetic tape is placed on or adhered to the floor. If the robot recognizes the magnetic tape, it will not run on it. All of these solutions have the disadvantage that they limit the user's freedom of designing the living space and are very inflexible.

  In the case of an autonomous mobile robot that stores and manages a map of the area of use for subsequent use, the virtual interrupted area can be recorded directly on the map. These can be, for example, virtual boundaries that the robot must not pass through. The advantage of this purely virtual blocking area is that it does not require additional markings around the robot. However, due to a user error or a robot measurement and running error, the robot may be present in an area where the user actually intends to shut off the robot, causing unintended damage. In addition, the input of the virtual blocking area must be as simple as possible, but it must be easy to understand.

  The object underlying the present invention is to make the operation of an autonomous mobile robot, in particular the operation of the blocking area, simple and robust.

  The above object is achieved by a method according to claims 1, 6, 18, 24, 30, 34, 37 and 58, an autonomous mobile robot according to claim 66, and a system according to claims 27 and 61. You. Various embodiments and further developments are the subject of the dependent claims.

  A method for controlling an autonomous mobile robot configured to uniquely navigate within a robot usage area using sensors and a map is described. According to an embodiment, the method includes detecting an obstacle based on measurement data obtained from the sensor, determining a position of the detected obstacle, and avoiding a collision with the detected obstacle. Controlling the robot such that the map includes map data indicating at least one virtual blocking area, and the at least one virtual blocking area is used when controlling the robot. Is characterized in that obstacles detected in the same manner are considered in the same manner.

  Furthermore, a method for controlling an autonomous mobile robot is described, wherein the robot is configured to uniquely navigate within a robot usage area using sensors and a map, wherein the map defines at least one virtual boundary line. The at least one virtual boundary has a direction such that a first side and a second side of the at least one virtual boundary can be distinguished, and the navigating of the robot includes Crossing of the boundary line in a first direction coming from a first side is avoided, while navigating the robot while moving the boundary line in a second direction coming from the second side of the boundary line. Crossing is allowed.

  Furthermore, a method of controlling an autonomous mobile robot is described, wherein the autonomous mobile robot is configured to independently navigate in a robot usage area using a sensor and an electronic map, and the robot is configured to self-locate in the map. May be periodically determined, and the map may include at least one virtual blocking area. The method of an embodiment comprises the step of checking whether the blocking area is active or inactive based on a predefinable criterion, wherein the robot considers only the active blocking area, As a result, the vehicle does not travel in the active cutoff region.

  According to one embodiment, the method comprises: receiving data representing a virtual occlusion region from another robot via a communication connection; and storing the virtual occlusion region on a map of the robot based on the received data. And

  Further, a system having an autonomous mobile robot and an external device is described. The robot automatically navigates its environment based on the map data, detects a situation in which the robot cannot automatically release itself, and sets the state of the robot in response to this detection. It is configured. The external device is configured to send an inquiry to the robot via at least one communication connection to query the status of the robot. The robot may further emit an optical and / or acoustic signal for a predetermined time if the state of the robot at the time of receiving the inquiry from the external device indicates that the robot cannot release itself automatically. Is configured.

  Further, a method for controlling an autonomous mobile robot configured to uniquely navigate within a robot usage area using sensors and an electronic map is described. The robot periodically determines its position in a map, and the map may include at least three different classification regions. In one example, the method comprises: determining a position of the robot using the sensor to determine its position; and checking that the robot is in any of the at least three different classification regions. Automatically navigating to perform a task if the robot is in a first area of the at least three different classification areas, and if the robot is in a second area of the at least three different classification areas; A third area of the at least three different classification areas that does not automatically navigate to perform a task is a virtual blocking area in which the robot does not automatically travel.

  A method for exchanging information between at least two autonomous mobile robots is described, wherein each of the at least two robots autonomously navigates a robot usage area using a sensor and an electronic map, and automatically maps the map. Configured to create and update. Each robot has a communication module that can transmit information to at least one other robot. According to one embodiment, the method includes automatically determining an operation of transforming a first robot's first map coordinates into a second robot's second map coordinates; Transmitting position-related information from the first robot to the second robot; and converting the coordinates of the position-related information of the coordinates of the first map into the coordinates of the second map using the conversion operation. And Further embodiments relate to a robot configured to perform the methods described herein.

  A method of inputting a virtual cut-off area into an electronic map representing a robot use area of an autonomous mobile robot is described. In one embodiment, the method comprises accepting user input from a human-machine interface to define the virtual occlusion region; and evaluating the user input, wherein the user input comprises at least one predefined Checking whether the virtual criterion is stored on the map and / or in what geometric form, based on the evaluation of the user input, Determining.

  A method for controlling an autonomous mobile robot configured to uniquely navigate within a robot usage area using sensors and an electronic map is described. The robot periodically determines its position in the map, and the map may include at least one virtual blocking area where the robot does not travel. According to one embodiment, the method comprises the steps of: detecting a dangerous area when navigating the robot usage area where the function of the robot is at risk or limited; Automatically defining a surrounding blocking area; and storing the blocking area on the map. Further embodiments relate to a robot configured to perform the methods described herein.

  An autonomous mobile robot configured to automatically navigate a robot use area based on map data, and a projector configured to project information onto a floor or an object in the robot use area. A system is described. The system is configured to extract position-related information from the map data together with a relevant position, and project the position-related information by the projector onto a corresponding position of the floor or an object on the floor.

  Finally, an autonomous mobile robot is described. In one embodiment, the robot automatically navigates a robot usage area based on map data, receives position-related information from a user via a human-machine interface, determines a robot path based on the information, It is configured to move along this. After or after the robot moves along the robot path, the location-related information input by the user is discarded or recognized as valid and is permanently stored with the map data.

  The operation of the autonomous mobile robot, particularly the operation of the blocking area, becomes simple and robust.

FIG. 2 is a diagram illustrating a system including an autonomous mobile robot, a human-machine interface, and a server that can communicate via a network connection. It is a block diagram which shows the structure of an autonomous mobile robot, and the communication possibility with another (external) device. FIG. 4 schematically illustrates some possibilities for inputting location-related information when defining a virtual blocking area by a map displayed on a human-machine interface. FIG. 4 is a diagram illustrating a virtual cutoff area around an obstacle where the maximum dimension cannot be easily detected by the robot. FIG. 9 is a diagram illustrating an example in which position-related information such as a virtual blocking area is expressed by projecting the information on a floor. It is a figure showing an example which protects a dangerous place, such as a stairway or an obstacle, using a virtual boundary line. FIG. 7 is a diagram illustrating an example of information exchange between two robots in which position-related information such as a virtual blocking area is exchanged. FIG. 4 is a visualization of different approaches for an autonomous mobile robot to navigate out of a virtual block area.

  The invention will be explained in more detail with reference to the examples shown in the figures. The figures are not necessarily to scale and the invention is not limited to the embodiments presented. Rather, emphasis is placed on representing the principles underlying the invention.

  As a service robot, an autonomous mobile robot automatically performs one or more tasks such as cleaning and monitoring a robot usage area and transporting an object in the robot usage area (such as an apartment). The embodiments described herein relate to a cleaning robot. However, the present invention is not limited to a cleaning robot, and can be applied to an application in which an autonomous mobile robot executes a task in a defined use area and can automatically move (or navigate) on a map.

  FIG. 1A shows an example in which the autonomous mobile robot 100 is incorporated in a home network that is a wireless network (WLAN). In the present embodiment, the WLAN access point 501 allows the robot 100 to communicate with the human-machine interface (HMI) 200, similarly to the external computer 502 (for example, a cloud server) that can reach the Internet 500. FIG. 1B shows, by way of example, a block diagram of various units (modules) of the autonomous mobile robot 100 of FIG. 1A. In this case, the unit may be an independent module or a part of software for controlling the robot. Software responsible for the behavior of the robot 100 (including the control software module 151 and the navigation module 152, see FIG. 1B) may be executed (by a corresponding processor 155 and memory 156) on the control unit 150 of the robot 100. The control unit 150 may perform some operations, at least in part, with the help of an external computer. That is, the computing power required by the control unit 150 can be at least partially outsourced to an external computer reachable, for example, via a home network or the Internet (cloud).

  Robots operate essentially autonomously. For example, the robot has a base station 110 that automatically returns after completing a task to enable work without multiple interactions with the user. This allows, for example, the robot to charge the battery or (in the case of a cleaning robot) dispose of the collected dirt.

  The autonomous mobile robot 100 includes a drive unit 170 having, for example, an electric motor, a transmission and wheels, so that the robot 100 can at least theoretically aim at each point of its area of use. The drive unit 170 can be designed, for example, to convert commands or signals received from the control unit into movements of the robot 100.

  The autonomous mobile robot 100 includes a communication unit 140 for establishing a communication connection 145 to a human-machine interface (HMI) 200 and / or another external device 300. The communication connection may be, for example, a direct wireless connection (eg, Bluetooth®), a local wireless network connection (eg, WLAN or ZigBee), or an Internet connection (eg, to a cloud service). The human-machine interface 200 includes information about the autonomous mobile robot 100 (eg, battery status, current work instructions, map data (ie, information stored on the map, and thus location-related information), such as a cleaning map, etc.) and user commands. Can be displayed, and a work instruction of the autonomous mobile robot 100 can be accepted.

  Examples of the human machine interface 200 are a tablet PC, a smart phone, a smart watch, a computer or a smart TV. The human-machine interface 200 can also be integrated directly with the robot, such that it can operate the robot via, for example, hitting keys, gestures, and / or voice input / output. Examples of external devices 300 are computers and servers to which calculations and / or data are entrusted, external sensors that provide additional information, or other appliances that cooperate with or exchange information with autonomous mobile robot 100 (eg, other Autonomous mobile robot 100B).

  The autonomous mobile robot 100 may have a work unit 160 such as a cleaning unit (for example, a brush or a suction device) for cleaning a floor or a gripping arm for gripping and transporting an object. In some cases, another unit, such as a telepresence robot or a surveillance robot, is used to perform the desired task, and the working unit 160 is unnecessary. Thus, the telepresence robot comprises a multimedia unit consisting of, for example, a microphone, a camera, and a screen, and enables a communication unit coupled to the human-machine interface 200 to enable communication between a plurality of persons far apart from each other. It has a unit 140. In the surveillance robot, an abnormal event (eg, fire, lighting, unauthorized person, etc.) is detected in surveillance traveling using a sensor, and this information is notified to, for example, a user or a control point.

  The autonomous mobile robot 100 may include one or more sensors to obtain information about the robot's environment (environment), such as the location of obstacles or other navigation features (eg, landmarks) within the robot usage area. And a sensor unit 120 such as a sensor. Sensors for obtaining information about the environment include objects (eg, walls, obstacles, etc.) in the robot's environment, such as optical and / or acoustic sensors that measure distance by triangulation or transit time measurement of the emitted signal. Active sensors (triangulation sensors, 3D cameras, laser scanners, ultrasonic sensors) that measure the distance to the camera. Other typical examples of suitable sensors are passive sensors such as cameras, tactile sensors for obstacle detection, ground distance sensors (eg, detecting falling edges, stair steps, etc.), speeds such as odometers, etc. And / or sensors for determining the distance traveled, inertial sensors (acceleration sensors, yaw rate sensors) for determining changes in the position and movement of the robot, and wheel contact switches for detecting contact between the wheels and the ground.

  The control unit 150 described above may be configured such that the autonomous mobile robot 100 moves autonomously in its area of use and provides all functions necessary to accomplish a task. To this end, the control unit 150 includes, for example, a processor 155 and a memory 156 for executing control software of the robot 100 (see FIG. 1B, control software module 151). The control unit 150 generates a control command or a control signal for the working unit 160 and the drive unit 170 based on the information supplied from the sensor unit 120 and the communication unit 140. The drive unit can convert these control signals or commands into robot movements. The control software module 151 may include software functions for object recognition and task scheduling. The navigation module 152 is provided as a separate software module so that the robot can perform tasks autonomously. The navigation module 152 may include software features for robot navigation (eg, map management, map-based path planning, robot self-localization within a map, SLAM algorithm, etc.). Of course, the control software module 151 and the navigation module can interact, share information, and collaborate. This allows the robot to navigate and navigate in the environment using navigation features such as landmarks. The navigation module 152 operates, for example, with one or more maps of obstacle avoidance strategies (obstacle avoidance algorithms), simultaneous localization and mapping (SLAM) algorithms, and / or robot usage areas. In particular, obstacles are detected by sensor measurements and their positions are determined. The position of the obstacle can be stored in the form of map data. Since these methods are already known, the description is omitted here.

  The map of the robot usage area can be recreated by the robot during use or by using an existing map at the start of use. The existing map may have been created by the robot itself during a previous use, such as a reconnaissance run, or may have been provided by another robot and / or a human, and is permanently stored in, for example, non-volatile memory 156. . Alternatively, the permanently stored map of the robot area is stored outside the robot, for example, on a computer (tablet PC, home server, etc.) in the home of the robot user or a computer accessible via the Internet (eg, a cloud server). Can be saved. In the example of FIG. 1, the map is included in the navigation module 152. The map used by the robot is typically an electronic map, which typically includes a collection of map data representing location-related information. Thus, a map represents a plurality of data records along with map data, which can include location-related information such as lines and other geometric objects (such as area elements). These lines represent, for example, the contour of the obstacle (detected by the robot). However, the map data includes not only the geometrical object and the position in the robot use area, but also information about the meaning and the attribute of the object input to the map. For example, one or more attributes (properties) can be assigned to objects entered on the map. Therefore, certain (partial) areas of the map may have attributes such as "not cleaned" or "cleaned" and / or "carpet" or "parquet" and / or "blocked by obstacles". Can be assigned. Other attributes may include, for example, classifying the (split) area as "kitchen" and assigning a time interval during which the area should be cleaned.

  In general, an electronic map that can be used by the robot 100 is a collection of map data for storing location-related information about the robot's use area and the environment associated with the robot in this use area. One type of location-related information that can be stored on a map is information about the location of an object within the robot usage area. Such objects are, for example, walls, doors, furniture, and other movable and immovable objects that a robot may (at least theoretically) collide with. Further, the robot base station 110 may be an object recorded on a map. The position of an object (obstacle) is usually defined by coordinates. Another type of map data is location-related for performing tasks of the robot 100, such as, for example, which area parts have been processed, particularly cleaned, or which position (in the robot area) the robot has approached during its operation. Information. Another type of position-related information is to divide the robot usage area into a plurality of spaces and sub-areas. This division may be performed automatically by the robot 100 or with the aid of a user. The user can make the split manually or manually modify the split performed automatically. In addition, space names (eg, “room 1”, “room 2”, “hallway”, “kitchen”, “living room”, “bedroom”, etc.) can be included in the map data. Various robot usage areas, such as different floors of a house, can be stored on different maps.

  Furthermore, the navigation module 152 is configured such that the virtual blocking area S can be marked in the map, so that the robot does not automatically run and / or pass through this area during navigation. This occurs, for example, when the area marked as the virtual cutoff area S is treated by the robot control unit 150 as if the cutoff area S is an obstacle in the use area of the robot 100. Therefore, to prevent the blocking area S from being traveled by the robot 100, the control unit 150 of the robot 100 can utilize an obstacle avoidance strategy, also called an obstacle avoidance algorithm, which is detected. It is configured to control the robot based on the position of the obstacle such that collision with these obstacles is avoided. Based on the virtual blocking area S stored with the map data, the position of one or more blocking areas can be determined. These locations can be used in an obstacle avoidance strategy as if a real obstacle were standing at this location. Thereby, the robot 100 is handled so as not to automatically travel and / or pass through the virtual cutoff area S. This will be explained with the following example.

  Example 1: In a simple way to control an autonomous mobile robot, the robot responds directly to measured distances and relative positions to obstacles. For example, the robot travels straight until it is 1 cm in front of the obstacle and then changes direction. To apply these methods of controlling an autonomous mobile robot to a virtual occlusion region, the position of the robot in the map is determined, and based on the position of the occlusion region in the map, the distance (to the virtual occlusion region) and / or Alternatively, the relative position is determined. This is repeated at appropriate time intervals.

  Example 2: In another method of controlling an autonomous mobile robot, the robot determines the position of the obstacle, for example by distance measurement, and enters the position and, for example, the contour of the obstacle in the map into the map. On the basis of the map, the route of the robot is planned so as to travel around the obstacle and avoid collision. In order to apply these methods of controlling an autonomous mobile robot to a virtual occlusion area, the position of the occlusion area in the map is treated as an obstacle position at least during path planning.

  Example 3: In another method of controlling an autonomous mobile robot, work scheduling is performed based on a map. For example, in the case of a robot that performs floor treatment (for example, a cleaning robot that suctions, sweeps, or wipes), the floor on which to work is determined in the area to be worked. This may be performed before and / or during processing. Further, during processing, it can be determined which of the floor surfaces to be processed was actually processed. When determining the floor surface to be treated, it is considered that a floor part where an obstacle exists or a floor part which cannot be accessed due to the obstacle does not need to be treated or cannot be treated. In order to apply these methods of controlling an autonomous mobile robot to a virtual occlusion area, at least the position of the occlusion area in the map during work scheduling is treated as an obstacle position. This means, in particular, that the surface occupied by the blocking area, such as the surface occupied by obstacles, is not added to the surface to be treated.

  Example 4: In some cases, it may be advantageous to treat the blocking area as a real obstacle for only part of the control method. Many commercial home robots are circular and can rotate on-the-fly without the risk of hitting obstacles. For more complex geometries, such as one or more corners (especially substantially triangles), this is no longer guaranteed. Therefore, in order to control the robot so as not to cause a collision, it is necessary to check whether or not a collision occurs after the rotation and during the rotation for each rotation in the place. In order to simplify the control of such robots, it is proposed to treat the virtual blocking area as an obstacle during the translational movement of the robot and ignore the blocking area during rotation of the robot on the spot ( In contrast to real obstacles).

  Generally, the virtual blocking area S is a floor surface on which the robot must not travel. The floor may be surrounded by a virtual boundary B and an actual obstacle. In some cases, for example, a virtual boundary B may close the robot deployment area to prevent the robot from passing through an open (house) door. In either case, the virtual boundary B is characterized in that the region where the robot can travel is divided into a region where the robot can travel freely and a region where the robot is prohibited from traveling.

  The virtual blocking area S can be stored, for example, by storing a virtual boundary B or as a floor with map data. For example, the map data is stored in the form of an occupancy grid map in which the robot use area is represented by a grid of cells, and information on whether or not a specific cell is occupied by an obstacle for each cell is stored. To mark a blocked area S in the map, cells belonging to the blocked area S are marked as appropriately occupied cells.

  The virtual cut-off area S can be stored as a geometric basic figure such as a circle, a square, a rectangle, or a regular polygon, which has the advantage that the required storage space is reduced. For example, in the case of a circle, conservation of the center position and radius is sufficient. To allow for more complex geometric shapes of the virtual occlusion region S, the virtual boundaries B of the virtual occlusion region S can be stored, for example, in the form of polylines. For the virtual boundary B, a floor area where the robot needs to be blocked can be stored. For this purpose, the orientation can be preserved with respect to the virtual boundary B, so that it is possible to distinguish on which side of the virtual boundary B the robot needs to be (for example always on the right side of the boundary B). In particular, it can be determined whether the robot approaches the virtual boundary B from a first direction or a second direction (ie, for example, from left or right), where the second direction is opposite to the first direction. It is. This is done, for example, by storing the polyline as a directed segment or vector having a start point and an end point. Therefore, for example, it can be defined that the right side of the boundary B can pass.

  The virtual boundary B is handled so as to be able to get over the free-flowing floor from the blocked floor, but is blocked in the opposite direction. That is, when the robot approaches the virtual boundary B from a first direction (eg, from the right), the virtual boundary B considers that the robot does not automatically travel and / or pass. For example, virtual boundary B is treated as an obstacle (as described above). Thus, the robot uses an obstacle avoidance algorithm for navigation, which is detected by the robot's sensor when the robot approaches an occluded area defined by the boundary (ie when coming from the right). Consider the virtual boundary B in the same way as the real boundary of the real obstacle shown. If the robot approaches the virtual boundary B from a second opposite direction (such as from the left), there is no effect. The robot can pass through the virtual boundary B.

  At this point, such a virtual boundary B can also be used temporarily, in addition to the permanent delimitation of the virtual blocking area. For example, it can be used to delimit sub-regions where a robot performs a particular task (such as cleaning). Virtual boundary B is active until the robot completes or interrupts the task. This has the advantage that the robot can enter the area to be processed. No additional complex control procedures are required to keep the robot in the area to be processed (since everything outside the area to be processed is defined as a virtual blocking area in this example). In the simplest case, only the obstacle avoidance strategy and the strategy for completing the task in a closed space are used by the robot controller 150.

  (Definition of Virtual Blocking Area) In order to add the virtual blocking area S to the map data, user input is performed through the human machine interface 200 (HMI). Information input by the user to the HMI 200 for the virtual blocking area S is evaluated according to predefinable criteria. For example, it can be determined based on this evaluation whether the blocking area S is stored and / or in what form. This procedure is illustrated in the following example shown in FIG.

  FIG. 2 illustrates, as an example, input of the virtual cutoff region S via the HMI 200 (for example, a tablet PC). To this end, the HMI 200 is adapted to display map data in the form of a human-readable map. On this map, the user can enter information about the newly defined virtual blocking area S.

  FIG. 2A shows the input of a new blocking area S by a (two-dimensional) geometrical shape such as a square, a rectangle, a parallelogram, and a circle. The size and direction are determined, for example, by the position of the user's finger on the touch screen 201 of the HMI 200. The direction of the basic graphic can be determined by the user. Alternatively, the orientation may be determined based at least in part on the map data. For example, one side of a basic shape (eg, a square) can be parallel to a nearby wall. The position and size of the blocking area S may be determined by the user, or may be determined at least partially based on existing map data. Therefore, for example, the virtual blocking area S registered in the corner of the room can be enlarged and / or moved so as to be closed by the wall. This is particularly effective when the area between the wall and the blocking area S is smaller than the space required for the robot to navigate.

  FIG. 2B shows the setting of the cutoff region by the virtual boundary B. For example, a user can deny a robot access to a corner of a room by defining a virtual boundary B in the form of a straight line or a polygon (open or closed). The so-defined blocking area S is defined by the virtual boundary B and the wall. In response to a user input on the touch screen, it is analyzed whether the virtual boundary B should block the floor, and in some cases, which floor should be blocked. For example, the HMI 200 can check whether or not the virtual boundary B input by the user divides the robot use area displayed on the map into at least two consecutive sub-areas. This is the case, for example, when the virtual boundary B is represented by a closed polygon chain, or when the virtual boundary B connects two or more obstacles (for example, two walls intersecting a corner of a room). In this case, the divided region of the robot use region includes all possible positions that the robot can reach from positions in the divided region without passing through the virtual boundary B. This reachability can be determined, for example, using a path planning algorithm. To divide the robot use area into at least two divided areas (virtual cutoff area S and the rest of the robot use area), such as a room with two doors each closed by a virtual boundary B for robot 100 (A segment of the virtual boundary B) may be required.

  If the robot usage area is subdivided into at least two consecutive parts, it is automatically determined which consecutive parts need to be cut off. A possible criterion for this is that the largest contiguous part where the base station 110 and / or the robot 100 is located is considered as the area of use, and all other contiguous parts are stored accordingly as the virtual blocking area S. is there.

  If a definitive decision cannot be made automatically for the newly created virtual blocking area S (e.g., because the user input is ambiguous, illegible or ambiguous), a warning and / or inquiry to the user is made. be able to. For example, the user can define an area where the base station 110 of the robot is located, for example, the upper right corner of the room shown in FIG. Analysis of the user input will determine that there is a large portion and a very small portion (the corner of the room) and that it is in a small portion of the base station 110 of the robot 100. This segmentation can be considered plausible, and the area that the user actually wants to block is unclear. The user can be informed of this fact via the HMI 200 (eg, by a message on the touch screen), giving the user an opportunity to determine that he accidentally shut off the wrong corner of the room. Alternatively, one or more newly created virtual cutoff areas S can be selected from the automatically determined partial areas. In some cases, the user can set the base station to a new location and notify robot 100 with appropriate user input.

  FIG. 2C illustrates another example of a method in which a user defines a virtual cutoff region. According to this, the user can define the virtual blocking area S by the planar marking. This occurs, for example, by a finger wiping action. The input of the user here is very coarse, and it is necessary to analyze where the appropriate virtual boundary B of the virtual blocking area is. This is done, for example, by forming a convex hull around the planar mark or by covering the planar mark with one or more rectangles (or other basic geometric figures). This can be, for example, a rectangle of the smallest area surrounding the area mark. Further, obstacles stored in the map data can also be considered. For example, one side of the rectangle can be placed parallel to a nearby obstacle (such as a wall).

  FIG. 2D shows another example of a method in which a user defines a virtual cutoff region. According to this, the user can set the blocking area based on an obstacle (such as a wall) or another landmark. For example, the user touches an obstacle on the touch screen and drags a desired distance from the obstacle to expand the virtual cutoff area S. According to this procedure, it is easy to define the virtual cutoff area S so that the robot 100 maintains a certain distance to each obstacle. Additionally or alternatively, the user can directly set the distance to the obstacle (eg, 85 cm). Analyzing the user's input to define the virtual boundary B and thus the virtual occlusion region S from the parameters entered by the user (e.g. distance to obstacles), specified obstacles and possibly other adjacent obstacles It is necessary to judge whether it can be determined.

  The virtual blocking area S defined at a certain distance from an obstacle (particularly a wall) does not necessarily need to extend along the entire length of the obstacle. The user can further restrict the blocking area. This can be done, for example, using concatenation. For example, to occlude a corner area of a room (with two walls), a user can determine a first distance to a first wall and a second distance to a second wall. The connection (intersection) of these two regions thus defined is the desired blocking region S. This has the particular advantage that the virtual blocking area can be determined very accurately by the user.

  The obstacle that the robot 100 must observe the user-definable distance does not necessarily have to be a wall. As an example, FIG. 3A is a diagram illustrating a bar stool H in which the base of the autonomous mobile robot 100 is difficult to navigate and difficult to detect. As shown in FIG. 3B, defining a virtual cut-off region S starting from a bar stool portion that can be detected as an obstacle H is advantageous in that the robot 100 automatically avoids the base portion of the bar stool H in the future. There may be points. In this case, the blocking surface is, for example, a circle whose center and diameter are determined based on the position and size of the base portion of the bar stool. Since the position of the bar stool is not fixed, there is no fixed position in the so-defined blocking area S as well. Rather, the position of the blocking area S is determined during use of the robot based on sensor measurements of the robot 100. For example, a robot with a camera and image recognition can recognize a bar stool as such. Alternatively, it can be stored together with the map data. For example, in a partial area around an obstacle of a given size (corresponding to the detectable part H of the bar stool) (where the bar stool is usually), it is necessary to take into account the virtual blocking area S around the obstacle. . The virtual blocking area is not stored in absolute coordinates in the map, but is stored relative to the obstacle. When the position of the obstacle changes, the virtual blocking area moves accordingly.

  In the approach described here, the position of the virtual blocking area S is stored not in the global coordinates of the global coordinate system used for robot navigation, but in a local reference (that is, relative) to an obstacle or a landmark. In this way, in this case, since the virtual blocking area S is based on the current sensor measurement, a robust consideration of the virtual blocking area S and accurate running along the virtual blocking area S are possible. Thus, by way of example, a user can block an area that is only a few centimeters wide (eg, 5 cm) parallel to any wall. As in the example of the bar stool (see FIG. 3), it is possible to define a virtual blocking area S that moves in accordance with a change in the position of an obstacle or a landmark in the map. The change in position may be achieved, for example, by moving (eg, pushing) an obstacle in the environment or by modifying the position plotted in the map data (eg, of a measurement error).

  The input of the information on the virtual cutoff area S does not need to be based only on the map display. For example, the HMI 200 may be configured to recognize a user gesture. For example, the user can directly describe the outline of the virtual blocking area S (on the blocking area). For example, to detect gestures, use a camera or 3D camera that can be integrated into the robot. At this time, in order to determine the virtual boundary B and the blocking area S, the user's input needs to analyze where the user is located and the location indicated by the appropriate gesture of the user.

  As a further option, information about the virtual blocking area S can be input during the learning run of the robot 100, and the analysis of the input information also takes into account the current position and orientation of the robot. Therefore, the user can indicate an area to be avoided while the robot 100 is searching for its own use area for the first time. This is performed, for example, according to the position and orientation of the robot. Therefore, the user can point out that the area of the corner of the room where the robot is currently heading is the virtual cut-off area, for example, by voice inputting “Stop, do not run this corner”. Similarly, the user can instruct the robot to maintain a distance determined by the user with respect to the obstacle searched by the robot. The input of this information can be done via a predefined command of the HMI 200 (such as a remote control or tablet PC). As mentioned above, the input of information (alternatively or additionally) can also take place in the form of voice commands recorded and analyzed via a microphone integrated into the robot 100 or the HMI 200 or via an external microphone. Alternatively or additionally, further aids for inputting information can be used. For example, a line can be projected onto the floor using a laser pointer configured to generate the line. The robot can detect its position and how it extends by using, for example, a camera, and store it as a virtual boundary B of the virtual cut-off area S together with the created map data. Alternatively or additionally, conventional markings, such as magnetic tape or infrared barriers, can be used during the learning run to inform the robot about areas that must not be run. The robot searches for how to extend using the sensor, and stores the corresponding virtual cut-off area S together with the generated map data. Thus, the marker can be deleted again after the learning travel.

  Confirmation of user-defined occlusion region-The virtual occlusion region S created based on the information received from the user may cause unexpected and undesirable behavior of the robot. Therefore, it is important not only to analyze the information input by the user in relation to how much the virtual blocking area S desired by the user has been determined, but also how the blocking area affects the function of the robot. For this purpose, for example, a number of criteria can be checked, and in the case of their non-performance (or violation), the storage of the virtual interception area S is rejected or performed only after explicit confirmation by the user. Will be Before that, corresponding information on the reason why the virtual blocking area S is not saved can be sent to the user.

  Thus, for example, it can be checked whether the robot is located partially and / or completely in the newly created virtual blocking area S. If so, the user may be notified and asked how the robot 100 should handle it. Therefore, storage of the virtual cutoff area S can be omitted. Alternatively, the user can save the virtual blocking area S and instruct the robot to leave it. In another alternative, the user may instruct the robot 100 to stop and later remove it from the occluded area.

  Furthermore, it is possible to check whether the robot can effectively execute the planned task and / or can autonomously approach the important place of the robot function in consideration of the virtual blocking area S. This includes, for example, that the robot 100 can approach the base station 110 from its current location and that the base station 110 is not in a blocked area. In addition, it is possible to check, for example, starting from the current robot position and / or the base station 110, whether it is possible to gain further unobstructed access to the robot use area that does not belong to the blocking area. Therefore, for example, if the blocked area S cannot access another area of the used area larger than the maximum size that can be defined in advance, if it can be reached only through a large detour, for example, the storage of the virtual blocked area S can be prevented. . In particular, the robot use area can be subdivided into a plurality of divided areas corresponding to, for example, a room of a house or a part thereof. When such a divided area cannot be accessed (that is, is blocked) by the virtual block S, the user can be notified of this. The user can reconfirm the storage of the virtual cut-off area S despite the severe restrictions on the robot usage area, and obtain the possibility of permanent storage.

  Known path planning algorithms can be used to determine whether a particular area can be reached or blocked. Thus, for example, if a newly created virtual blocking area is considered and cannot travel and / or pass by itself, it can be determined whether a path from the current robot position to the base station 110 exists. In a similar manner, it can be determined whether or not a route from the base station to this partial area exists for all parts of the robot use area. In particular, if the corridor connecting to this area is smaller than a predefinable threshold, the area of the map is considered to be unusable or blocked. For example, the threshold value, in addition to the diameter of the robot, corresponds to the safety margin required for the robot to navigate and control a safe and reliable corridor. This safety margin may correspond to the maximum location uncertainty of the navigation module 152, which is determined, for example, during the SLAM method.

  If it is detected that another partial area of the robot area is inaccessible by the virtual obstruction area S, it is further determined whether a slight modification of the virtual obstruction area S makes the inaccessible partial area accessible again. You can check. For example, entering data via a map is often inaccurate, and a slightly modified occlusion region still meets the wishes and needs of the user. For example, if the corridor to the area behind it, which is limited by the blocking area S, is only as wide as the robot itself, a slight reduction in the blocking area allows access to the area behind. For example, the virtual boundary B is moved or deformed to check whether a slight change in the virtual blocking area S meets the criteria. For example, if a virtual boundary is provided by a polygon chain (open or closed), the vertices of this polygon chain can be moved.

(Area without Work Request) An area where the autonomous mobile robot 100 may cause damage is not always completely excluded from the navigation by the robot 100 as the virtual cutoff area S. For example, this may be a hallway connecting all the rooms that the robot 100 cleans. This corridor requires the robot 100 to travel. Otherwise, the task cannot be performed in another room. In addition, shoes are often placed in the corridors, and the shoelaces may wrap around an actuator such as a rotating brush. As a result, on the one hand, the shoes may be damaged and the robot 100 may be hindered in performing its task. Another example is when a delicate carpet that the robot 100 cannot handle with an actuator such as a brush is placed in a central area that the robot 100 cannot avoid.

  Given the issues described, it may be helpful to exclude corridors from autonomous processing. Thus, the robot can be configured to distinguish at least three categories of the virtual area. In the first category of virtual areas, the robot can automatically navigate and execute defined tasks. In the second category of virtual areas, the robot can autonomously navigate, but does not perform tasks independently. The area of the third category is the above-mentioned blocking area. When navigating the robot 100, care is taken that the robot 100 does not independently travel and / or pass through a third category of area.

  The definition of the virtual area is performed by the user, for example, as described above for the blocking area S. In particular, the user can be automatically suggested (by the robot or the HMI) to exclude the process of traveling through a virtual obstruction area that might impair the function of the robot. That is, the cut-off area is an area of the second category that can normally move but does not process the floor surface. Further, it can be assumed that the region belongs to the first category (that is, there is no restriction on the traveling performance and the work execution) until the user gives the reverse instruction.

  Furthermore, the robot travels as rarely and directly as possible in the area (second category) excluded from the processing when performing the task. Therefore, the robot travels in this area only when necessary for a task to reach the area behind the robot usage area. Then, the robot returns to this area only when the task of the robot is completed as much as possible. When traversing this area, care is taken to use the shortest and / or fastest methods. Alternatively or additionally, a route may be selected that keeps a predetermined minimum distance to the obstacle as far as possible. If the robot cannot maintain the minimum distance because it needs to pass between two obstacles that are less than twice this minimum distance, the path to select the distance to both obstacles as large as possible, especially A path that passes between the two obstacles is selected. Methods for realizing such a path are known per se. For example, path planning can use a cost function, in which costs can be determined based on, among other things, distance to obstacles, and the least cost path is ultimately used for robot control. Alternatively or additionally, a reactive control mode (eg, virtual force field (VFF)) can be used, in which the robot responds directly to the distance of surrounding obstacles.

  The latter can be realized, for example, in a task plan using a cost function. For example, the cost of traveling in the region excluded from the processing is set to be much higher than the cost of traveling in the region to be processed. For example, a one meter move in an area excluded from processing is evaluated as a ten meter move in the area to be processed. In doing so, the robot accepts that it will also make significant detours to avoid areas that are excluded from processing. The concept of using a cost function for the path planning itself is well known.

  (Display of Blocking Area) An important aspect of the virtual blocking area S is that the user can quickly, easily and directly see the effect of his settings. This is used, for example, where the display of a human-machine interface is in the form of a map. Since this map is a simplified representation of the robot usage area and therefore may be incorrect, direct re-entry of the virtual boundary B of the virtual blocking area S is advantageous. Also described here are other user inputs, such as entering user-defined subregions using virtual boundaries (eg, to quickly select them for later cleaning), or directly entering the region to be processed. This procedure is advantageous.

  According to an example, the robot 100 first receives location-related information, for example, regarding a virtual occlusion region, from the user's human-machine interface 200. From this position-related information entered by the user, one or more lines (eg, rectangles, open or closed polygon chains, etc.) representing, for example, a virtual boundary B of the blocking area S are determined (see FIG. 2). ). As mentioned above, the representation of the map of the robot usage area is an inaccurate abstraction of the real environment. Therefore, it is desirable to provide more realistic feedback (more realistic than a map representation) to the user about the effect of the blocking area defined via the HMI 200. In consideration of the user-defined blocking area S, the robot can determine a route and follow the route. The path can be passed once, several times, or until interrupted by the user. For example, the robot can move along a virtual boundary B of the blocking area S so that the blocking area does not travel and / or pass.

  The above-described visualization method can be applied not only to the occluded area but also to the divided area. In a newly defined sub-region (eg, part of a room) of the robot usage region, the robot can move directly along the (virtual) boundary of the sub-region. For example, in a user-defined area (in a room) to be cleaned, the robot can move along a virtual boundary within the work area to indicate to the user which area is to be processed. This realistic demonstration gives the user a direct impression of the effects of his input. The user can permanently store the input information or the map data (eg, polygon chain) derived therefrom via the HMI 200 and use it for future robot control. In addition, the user recognizes that his input does not produce the desired robotic motion and has the opportunity to modify the input or enter new location-related information. Modifications of user input can be directly translated into new modified robot paths (for new demonstrations with robots).

  Another way to provide users with quick, easy and direct feedback on their input is to project information directly into the environment. To this end, for example, laser projectors that specifically project lines, shapes, patterns, or images, drawn using a movable mirror and one or more lasers as light sources, onto an environment (eg, a floor surface) are described. used. The projector can be mounted on a fixed location in space, on the autonomous mobile robot 100, or on another autonomous mobile robot 100B.

  In the example shown in FIG. 4, the projector 190 is arranged on or integrated with the automobile robot 100. The configuration shown has the advantage that the projector 190 can be transported to (almost) any location in the robot field. In particular, the robot 100 can move to an appropriate place and perform projection therefrom. Therefore, based on the map data and the sensor data, it is possible to determine a position where necessary information can be projected to a desired place in the robot use area (particularly, the floor) without being disturbed by an obstacle. At this location, if it is determined that unobstructed projection to the desired location is not possible by the new obstacle or the user standing around, the robot 100 will take an alternative appropriate based on the map and sensor data. You can search for a suitable location.

  A feature of this approach is that location-related information (such as a boundary line, a basic geometric figure representing an occluded area, etc.) can be directly projected to the relevant location, and thus can be presented to the user in a concrete and easy-to-understand manner. For the calculation of the projection, the position and orientation of the robot 100 in the robot usage area are used. The position and direction can be known with high accuracy by the function of the autonomous mobile robot. In addition, the position and orientation of the projector 190 used in or on the robot 100 is already known by the structure of the robot. From now on, how to project light rays into the environment (or how to control mirrors and / or lasers) to reach points determined by map data in the robot's environment (especially the floor) Can be determined. Therefore, it is possible to extract the position-related information from the map data and display this at the corresponding actual position in the robot use area by the projector.

  In the manner described above, for example, a virtual boundary B (see, for example, FIG. 2B) can be visualized to the user by projecting it directly onto the floor. Additionally or alternatively, the virtual blocking area S can be made visible to the user by direct projection on the floor. Similarly, it represents, for example, a surface to be cleaned or a user-defined partial area. In addition, with the help of the projector 190, other map data, especially created by the robot 100, can be projected directly onto the robot usage area. This may be, for example, an area that has just been cleaned by the robot 100 or an area that will be cleaned next. For example, the user is warned of the danger of slipping on the area that has just been wiped.

  According to one embodiment, the information displayed by the projector 190 can be determined directly from the current position of the robot 100 and (optionally) its speed and / or its currently executing task. Thus, for example, a direct planned path of the robot can be projected on the floor. As a result, the user can predict the operation of the robot, and can avoid undesired disturbance of the work.

  Automatic Generation of Blocking Region-The virtual blocking region S need not necessarily be defined by the user through input via the HMI 200. The autonomous mobile robot 100 is configured to, for example, recognize the danger area as such, and independently define the cutoff area S based on this, in order to avoid the posted danger area in the future. ing. The at-risk region is a region that mainly affects the function of the robot or a region that is dangerous to the robot. For example, a robot can detect such an area simply by running using a sensor or analyzing a navigation function. This is explained in more detail by the following example shown in FIG.

  FIG. 5A shows a falling edge (such as a staircase) as an example of a danger area that can be detected only by traveling by the robot. Typically, the robot is equipped with a floor sensor 121 at the bottom to detect such a falling edge. These are arranged on the robot 100 so as to stop in time for the falling edge and avoid falling. However, malfunctions (such as dirt on the sensor) may always occur, and as a result, the robot 100 may not recognize the falling edge, and thus may move beyond the falling edge and fall (see FIG. 5 (B)).

  For example, to avoid the accident shown in FIG. 5B, the robot 100 may be used in a manner known per se, for example, during use (eg, learning execution or initial execution of a task, eg, cleaning) ( For example, it may be configured to detect the falling edge (by the sensor 121) and avoid it accordingly. An exemplary trajectory of the robot is shown, for example, in FIG. In this case, the robot 100 partially moves the falling edge until the floor sensor 121 detects it, and the position of the measurement point M is determined and stored. Then, based on these measurement points M and optionally other environment and map data, such as the trajectory T, the virtual boundary B and / or the virtual blocking area S, the robot takes into account the blocking area the position of the falling edge ( Particularly, the minimum distance d (for example, 1 cm) to the measurement point is maintained (see FIG. 5D). This allows the robot to clean along the falling edge and navigate so that it does not move beyond the falling edge. In particular, navigating so as not to need to trigger the floor falling sensor 121 taking into account the virtual blocking area S, thereby minimizing the risk of falling due to malfunction.

  In determining the virtual boundary B, consider that the position of the well-measured falling edge measurement point M has a maximum distance that is less than the robot diameter (otherwise, the robot will have two measurement points). Pass between them, and can recognize a runnable area or another area or receive detection of a falling edge). The falling edge may completely surround the (unable to travel) area or may be surrounded by an obstacle (wall, see FIG. 5C). Accordingly, the positions of the measurement points M are connected one by one. In some cases, the line thus obtained may be extended to an adjacent obstacle (eg, toward a wall). The line thus obtained delimits the surface driven by the robot from the surface that cannot be driven. A shift of the line in the direction of the already moved area leads to the above result, namely the virtual boundary B. This is just one of many ways to construct a virtual boundary B to ensure safety from falling edges. Another possibility is that each measuring point M defines a circle with a radius corresponding to the radius of the robot and the safety distance d. The overlapping circles are grouped in a cut-off area. The associated virtual boundary B is obtained by smoothing the outer contour (eg: convex hull (in pairs)). In this case, during navigation, the robot can be assumed to be a point (center of the robot's substantially circular outer contour).

  Another example of a situation where the robot can independently define the occlusion region relates to obstacles that the robot cannot recognize or difficult to recognize. For example, robots use active sensors that emit (eg, light) signals and receive reflections from obstacles for obstacle detection and mapping. For example, transparent obstacles, such as glass doors, reflective obstacles, such as mirrors, or obstacles that are outside the range of the radiated signal (such as low obstacles) are not recognizable or difficult to recognize. The robot detects these obstacles when the robot touches them using, for example, a tactile sensor (a sensor that detects physical contact with the obstacle). However, frequent and repetitive collisions with the robot's obstacles are not desirable by the user. Therefore, the robot can be configured to determine the position of an obstacle that can only be detected by touch (touch) while the robot is in use (learning or executing a task) and cannot be recognized by non-contact (for example, by an optical sensor). . From these positions, a virtual cutoff area S or a virtual boundary B is generated so that the robot does not touch and hold a predetermined distance d (for example, 1 cm) to an obstacle in consideration of the virtual cutoff area (falling edge Similar to the above example used). In this manner, the robot can clean around obstacles without contact. This minimizes the risk of damage to the robot or obstacle due to a collision.

  A third example of a situation where a robot can independently define an occluded area involves areas where it is difficult for the robot to navigate. This is, for example, a high pile carpet with many small obstacles on it, such as table and chair legs. This situation is difficult for the robot to handle, as traveling through the carpet is severely hindered, while at the same time the table and chair legs are actually mazes for the robot to navigate very accurately. . Thus, it may happen that the robot cannot get out of this situation, or that the robot can get out of this situation only after a long time has passed from this situation. The robot can detect this problem area by, for example, engaging in increased wheel slip and / or many driving maneuvers for a longer period of time in this area. To increase efficiency, this area can be a blocking area, which minimizes the risk that the robot will get stuck in this position in subsequent operations or consume a lot of time and energy . For example, cleaning of this area is performed only after an explicit instruction by the user.

  Before the automatically created virtual blocking area S is permanently stored with the map data, it can be displayed to the user. This makes it possible to determine whether the virtual blocking area S is permanently saved as proposed, or whether the robot needs to move to this area for subsequent use (albeit with a warning).

  The position of the automatically generated virtual blocking area can be linked to a landmark that can be easily detected by the robot. For example, the virtual boundary B in FIG. 5D can be stored as a connection line between walls serving as boundaries. In this case, for example, the edge functions as an easily recognizable landmark, for which the virtual blocking area S is stored. That is, the position of the blocking area S or the boundary line B is stored relatively to the position of a detectable landmark (for example, a wall) in the map. By directly linking to easily detectable landmarks, the position of the virtual occlusion region S is much more accurate and more accurate during navigation than if only known as global map coordinates for navigating the robot. Considered robustly.

  (Blockage Area Defined by Other Devices) When the first autonomous mobile robot 100 creates the virtual blockage area S, it may make sense to pass it to one or more other robots. Similarly, the robot 100 can receive the virtual blocking area S from the external device 300, particularly from the second autonomous mobile robot 100B. This situation is shown in FIG. 6 as an example. In this case, the first robot 100 can create the virtual cut-off area S, and not the first robot 100 that has created the virtual cut-off area S, but one or more other robots (for example, the second robot 100). (Eg, exclusively) by the robot 100B). To exchange information about the virtual blocking area S, the involved devices (first robot 100 and second robot 100B) use a communication connection that can be established via a communication unit 140 (see FIG. 1B).

  Similarly, the second robot 100B may have map data representing a robot use area. These may be the same data used by the first robot 100 or the data held, updated, and / or interpreted by the second robot 100B. When the robots 100 and 100B use different data sources, the coordinates of the position information on the map data of the first robot 100 can be converted into the coordinates of the position information on the map data of the second robot 100B (and vice versa). Similar). This conversion can be performed automatically on one of the robots 100, 100B, or on an external computing device such as a PC or cloud server. The parameters of the (coordinate) transformation can be determined automatically, for example, by a least squares method based on available navigation features, such as the position of the wall. In the simplest case, the (coordinate) transformation of a two-dimensional map consists of three parameters describing displacement (shift) (two parameters) and rotation (one parameter). For example, more complex transformations are conceivable to detect sensory (systematic) measurement errors or three-dimensional maps. For example, a sensor for measuring the distance of a first robot may systematically measure a smaller distance than a distance sensor of a second robot. This can be corrected with additional scaling parameters. In another example, attitudes (positions including directions) stored on both maps of the base station (or other navigation function) can be used to calculate the coordinate transformation. Assume that the pose stored in the map of the first robot is (albeit slightly) deviated from the pose stored in the map of the second robot. However, since both maps are the same real base station (the same real navigation features), the transformation operation (eg, shift and rotation) can be derived from the two poses.

  In an exemplary method in which information is exchanged between at least two autonomous mobile robots 100 and 100B, both robots 100 and 100B autonomously navigate within the robot usage area using sensors and electronic maps. It is configured to create and update maps autonomously. Both robots 100 and 100B have a communication module (see FIG. 1B, communication unit 140) that allows information to be transmitted directly or indirectly to other robots via external devices (eg, servers). According to the present example, the conversion operation from the coordinates of the first map of the first robot 100 to the coordinates of the second map of the second robot 100B is automatically calculated. This can occur on either of the two robots or on an external device (such as a server). The position-related information (map data) is transmitted from one of the robots (such as the robot 100) to another robot (such as the robot 100B). Before the transmission (in the robot 100), after the transmission (in the robot 100B), or during the transmission (in the external device for transmitting information), the operation of converting the position-related information of the coordinates of the first map into the coordinates of the second map is performed. Is converted using

  In addition to the above-mentioned user-defined virtual cut-off area S and the virtual cut-off area S automatically generated based on the functional failure and / or danger area (detected by the first robot 100), A virtual blocking area S based on work use (use of a robot to execute a task) can be used.

  For example, the user spills a liquid such as milk and asks the wiping robot to remove the puddle. In the example shown in FIG. 6, the first robot 100 is configured as a wiping robot configured so that the work module moistens and wipes the floor. While the first robot is engaged in the wiping operation, other robots (such as robot 100B) should not disperse the liquid through the puddle. Furthermore, other robots should not travel in areas that have just been wiped (and therefore wet). The first robot 100 will determine the area to be cleaned based on user input and possibly further sensor measurements. This robot can tell other robots in the home that this area to be cleaned should be treated (for example temporarily) as a virtual blocking area S.

  After the wiping robot 100 completes its activity, a notification indicating that the virtual blocking area S is released again can be transmitted to the other robot 100B. Alternatively or additionally, the virtual blocking area S can also have an elapsed time automatically. The wiping robot 100 can, for example, define a region W that has been newly wiped and thus still wet, as a blocking region S for another robot for a predetermined time, and block that region W (see FIG. 6). After this time has elapsed, the other robot 100B can automatically clear the virtual cutoff area S.

  (Activation / Deactivation of Blocking Area) The user may not want the robot 100 to always consider the virtual blocking area S. At the same time, the user may not always want to delete and create the virtual cutoff area S. Therefore, it may be useful to set a criterion and determine whether to take into account the virtual blocking area S when navigating the autonomous mobile robot 100 based thereon. That is, the robot can determine whether to independently travel or pass through the virtual cutoff area S based on a specific criterion.

  For example, the robot 100 may always consider the virtual blocking area S unless the user explicitly releases (eg, by the HMI 200) the blocking area S for a task or a predetermined time. For example, the virtual blocking area S is part of a dwelling that is used as a playground, and there are often small toy-shaped objects that damage the robot 100 during self-driving or self-contained activities such as floor cleaning. The user may wish to clean the playground at times, and may wish to clean it immediately or during the next work operation. For example, the user can notify the robot 100 via the HMI 200 that the virtual blocking area S needs to be cleaned immediately. The robot travels and cleans the virtual blocking area S for this work operation. The virtual boundary B can be used, for example, as a boundary of an area to be cleaned. In later work operations, the blocking area S is again considered.

  Alternatively or additionally, the user can inform the robot that the virtual blocking area S is inactive during the next work operation (especially house cleaning). For example, the robot can travel as if the virtual blocking area S is not stored, and can automatically clean the virtual blocking area S. Alternatively, according to the virtual boundary B, the robot can interpret the virtual cutoff region as a unique partial region to be cleaned and process it individually. In this case, for example, the virtual interrupted area can be driven with an increased priority. Also, an unexpected problem may occur at this location, and it is expected that the operation of the robot will be interrupted, so that the virtual cutoff area can run as the last partial area of the operation.

  Alternatively or additionally, the user can notify the robot that the virtual blocking area S is inactive for a predefinable time. For example, there are situations in which children who frequently play in a play corner in a children's room are absent for hours or days. During this time, the robot can consider play corners marked as virtual blocking areas S in the autonomous work plan. After the time specified by the user has elapsed, the virtual blocking area S is automatically activated again and is taken into account by the robot.

  In another example, activation / deactivation of the virtual blocking area S is automatically controlled by a calendar function. For example, the user may not want to control the robot to travel in the bedroom at night. However, during the day, for example, the robot is to clean the bedroom. In this case, for example, the time during which the virtual block S is active is recorded in the calendar, so that the virtual block area S is considered by the autonomous mobile robot 100 so as not to run or pass automatically. For example, the bedroom can be shut off from the robot during the night from 21:00 to 9:00.

  Calendar control provides a certain level of user comfort through automation, but is inflexible. The purpose of blocking the bedroom in the previous example is to avoid disturbing the sleeping user. Therefore, it is effective to link the activity in the blocking area directly to the activity of the user. However, especially in the example of a sleeping user, if possible, the robot should not travel in the bedroom to see if the user is (still) asleep. Thus, based on other devices 300, such as household items, sensors, and / or other robots, etc., whether the virtual blocking area S is considered (active) (eg, the robot is allowed to enter the bedroom) Is determined). Thus, for example, the sleep tracker's activity, bed sensor, or sleep mode of the activity tracker, a smart watch or other wearable fitness tracker can be used to determine if the user is asleep. Also, the activity of an electric toothbrush can be used. For example, when the electric toothbrush is used at night, the virtual cutoff region can be activated, and when the electric toothbrush is used in the morning, the virtual cutoff region can be deactivated. Numerous other scenarios are conceivable in which the activity of the virtual blocking area S is determined based on the state and / or information of the external device 300.

  Further, activation / deactivation of the virtual blocking area S may depend on the state and / or activity of the robot. For example, a robot can be equipped with various cleaning modules suitable for various dry and wet cleanings. In this case, the activity of the blocking area depends on the cleaning module used. For example, carpets or other water-sensitive floor surfaces may be treated as virtual blocking areas S when the wet cleaning module is operating. Another example of activation / deactivation of the virtual blocking area S according to the state and / or activity of the robot relates to a transport robot for home support. For example, a robot can carry a drink in an open glass. In this case, the robot should avoid uneven floor surfaces, for example, carpet edges. To achieve this, the carpet can be defined as a blocking area that is active as long as the robot transports the beverage.

  While the autonomous mobile robot performs work, particularly in the virtual blocking area S, the basis for determining whether the virtual blocking area S is considered when navigating the autonomous mobile robot 100 may change. In other words, the check whether the blocking area needs to be taken into account can be performed continuously or at least periodically, even during the work or the planning of the work. In such a check, if the robot determines that a blocking area to be considered has been added, the current position of the robot 100 may be located within the virtual blocking area S. In this case, for example, the robot stops and can wait for a user's instruction. Alternatively, the robot can travel out of this area. Alternatively, the robot may complete or at least partially complete the current task in the virtual blocking area before the area becomes active. For this purpose, for example, the time required to complete the task can be determined. If this time is less than the predefinable maximum, the task ends and the activation of the blocking area is delayed by this time.

  (Robot in Blocking Region) Usually, the (virtual) blocking region S is reliably avoided by the robot, for example, by being regarded as an actual obstacle during navigation. This approach works as long as the autonomous mobile robot 100 knows its location in the map with sufficient accuracy. However, if, for example, the user defines a partial area and identifies this as a blocking area while the robot is in this partial area, the robot may be able to enter the virtual blocking area S. Since the robot 100 does not always know its own position accurately, another problem may occur. As a result, the robot may pass unknowingly (virtually) over the virtual boundary. In that case, the robot may move to the blocking area and cause damage. Even when attempting to avoid collision, the robot may collide with obstacles. However, the robot may notice a navigation error due to the collision and adjust the navigation strategy accordingly. There is no immediate feedback in the virtual blocking area (due to physical collisions). Therefore, additional measures are needed to make the operation of the robot robust against such errors in the processing of the virtual blocking area. An example will be described below.

  One possibility for robust processing of the virtual blocking area S is to process the virtual boundary B such that one-way passage is prevented (as described above). As a result, the robot 100 can always leave the virtual blocking area while avoiding entry into the blocking area. In other words, the virtual boundary line B drawn on the map of the robot functions only in one direction. The virtual boundary can pass in one direction but not in the other.

  Alternatively or additionally, it can be ascertained whether the robot is completely or partially within the blocking area S. According to this check, it can be determined whether the robot leaves or stays in the blocking area S. For example, the blocking region can be divided into an edge region and a core region. If the robot is at least partially in the core area, the robot stops. If the robot is located only in the edge area of the blocking area S, the robot attempts to move out of the blocking area S. This function of the blocking area S (subdivision into edge areas and core areas) is figuratively known as a "soft wall". In other words, when the robot navigates, the blocking area does not have the effect of a “hard” wall, and the robot can enter, but then as a soft transition area that tries to exit the boundary area as much as possible Having. For example, a message is transmitted to the human-machine interface 200 to notify the user of the problem and wait for an instruction from the user.

  This confirmation can be continued during navigation each time the position of the robot is re-determined. Furthermore, this confirmation can be performed, for example, if a new virtual blocking area S has been defined and / or activated by the user or another device. If the robot is in the newly created virtual blocking area S, the storage can be refused until the blocking area S is confirmed by a user or the like. Additionally or alternatively, the robot is operated to automatically exit the blocking area S. Additionally or alternatively, the device (or user) that creates the blocking area S can be notified that the robot is in the newly created blocking area S. Further, an inquiry as to whether the robot can leave the newly created blocking area S and how to do so can be sent to the device (such as the HMI 200) or the user that created the blocking area S. For example, the user can specify a preferred direction for the robot to exit the blocking area. Alternatively, the user can stop the robot and carry it out of the blocking area by hand.

  In the case of the existing inactive blocking area S, the action information associated with the blocking area S can be stored. For example, a bedroom can be defined as a blocking area S that becomes active when the user sleeps. In this case, the robot can automatically leave the blocking area S after the blocking area S is activated. In other cases, it may be desirable for the robot to stop until the blocking area becomes inactive again or the user intervenes.

  The operating scenario of the autonomous mobile robot 100 may also include being moved manually by a user, typically resulting in the robot losing information about its location in the electronic map. The robot can then determine its position again by global self-positioning. Thus, the robot 100 moves within the environment to collect data about the environment using the sensors and compare them with existing map data. Since the robot has little or no information about its actual position relative to the map data during global self-localization, it may enter the blocking area S inadvertently. Therefore, it is important to check whether or not the robot is in the virtual cut-off area S after the global self-localization based on the stored map data.

  During self-localization, the robot moves to or near the virtual cut-off region S based on a position-determining hypothesis (ie, a hypothesis based on sensors and map data where the robot may be located, for example, determined by a probability model). You can check whether it is. Based on this information, the robot can adapt the exploration run to its global self-localization to reduce the risk (ie, possibility) of inadvertently running through the virtual occlusion region. The localization hypothesis based on the (global) self-localization probability of the robot in the map is known per se and will not be further described. What is important in this example is that if the robot does not know its position during self-location, it can only determine the probability of a particular map position. The robot can also check the probability of being in the blocking area. Depending on this probability, the robot can adapt the current route. For example, assuming the probability that the robot is in the blocking area S when the robot is moving along a specific route, the moving direction can be changed until the probability decreases again.

  In addition to determining whether the robot 100 is in the blocking area S, the path of the robot 100 can be recorded during global self-localization. Using this recorded path, it is possible to escape from the blocking area. For example, the robot can reverse the recorded path until it has left or is able to leave the occluded area.

  For example, the user wants to (exceptionally) clean this area, so that the user can intentionally or accidentally place the robot in the virtual blocking area S while moving. Starting from the position where the user has lowered the robot, the robot initiates a global self-localization (see above). Based on the distance traveled and recorded during the execution of the global self-localization, the starting position of the robot can be determined, thus determining whether the user has started the robot 100 in the virtual blocking area S Can be. Thereafter, the robot can execute a user-specified task in the virtual blocking area S. Further, the robot can transmit corresponding information (such as a warning message) to the user via the HMI 200.

  There are various approaches that can be used individually or in combination to determine whether and how a robot will move out of an occluded area. In FIG. 7A and FIG. 7B, the virtual blocking area S is divided into a first area Sa and a second area Sb. When the robot is in the first divided area Sa, the robot stops (emergency stop). When the robot is in the second divided area Sb, the robot travels so as to cross the virtual boundary B and go out of the cutoff area. The division of the virtual cutoff region S is performed so that, for example, starting from the virtual boundary B, all points within a distance d (for example, the width of the robot) belong to the second division region Sb. That is, the robot performs an emergency stop when the robot is farther than the predetermined distance from the boundary B, and autonomously escapes from the blocking area S when the robot is near the boundary B. The division of the virtual cutoff region S can be performed based on, for example, a user input. This can include the importance of complying with the blocking area. If it is very important to adhere to the blocking area, the width d of the second divided area Sb can be chosen to be very narrow (for example 1 cm) or omitted entirely.

  Another approach in which a robot moves out of an occlusion region is based on virtual force-field (VFF) analysis. Force field analysis is a method of controlling a robot reactively (known per se) without planned consumption (ie, without pre-planning the robot's path). For this purpose, a virtual force field "acting" on the robot is determined (calculated) based on the sensor readings and the robot's goals. In this connection, the terms force and force field are figurative. Therefore, it is not a physical force acting on the robot, but a virtual force. However, the robot's control unit 150 (see FIG. 1B) is configured to calculate these virtual forces, and the robot can respond to these forces (eg, in the direction of the virtual force acting on the robot). fall back). As with physical force fields, virtual force fields from various sources (obstacles, robot targets) can be added. Control commands for the drive unit are created based on the direction and magnitude of the resulting virtual force at the current position and direction of the robot. The control of the robot reacts directly to the sensor readings and there is no additional planned consumption. This force field analysis is used, for example (in the case of a soft wall), to efficiently navigate the robot out of the edge area of the blocking area S.

  As shown by way of example in FIG. 7C, for example, a virtual force field (represented schematically by a force vector V) always pointing to the next point of the virtual boundary line B is taken into account in the virtual cut-off region S. be able to. This approach is particularly suitable for quickly moving the robot out of the blocking area S if the robot enters the blocking area S during navigation, for example, due to incorrectly known positions of the robot. . In addition, the force field can be selected very large so that the robot does not travel in the virtual known area at the exact known position. For example, the selection is made in the same way as the actual obstacle, so that collision with the obstacle is largely avoided.

  Another approach is to select the lowest cost path to control the robot based on the cost of the robot's planned path. For example, if a certain amount is taken as “cost” for each distance traveled by the robot within the cutoff area S, and movement outside the cutoff area S does not generate a cost, the cost is minimized and cutoff is performed. The shortest path out of the area S is selected. Thus, the robot selects the shortest path out of the blocking area to minimize "cost". The term "cost" in this context should be understood figuratively and is also called a weighting factor.

  FIG. 7D shows the progress of the cost function of the route to the virtual cutoff area S as an example. Roads outside the blocking area S are inexpensive. When passing through the virtual boundary B, a basic cost C0 may occur. Thereafter, the cost increases in proportion to the moving distance. Of course, other cost functions can be used. If there is no schedulable path whose cost is below the predetermined maximum value Cm, the robot can be stopped, for example in an emergency stop state. As a result, the above-described division of the virtual cutoff region S is achieved implicitly.

  In the above approach, virtual boundary B behaves like a soft wall. Soft walls are characterized by the fact that their boundaries are not fixed, but are like flexible rubber bands. On the other hand, a hard wall, such as a real obstacle, cannot pass through (because it collides with a real obstacle) and is not provided. The robot stops immediately. With respect to the cost-based approach described above, this means that, for example, if the cost of the planned path that violates the virtual boundary B is lower than the cost of all other possible movements of the robot, the virtual boundary B and thus the occluded area It means that you can (partly) navigate. For example, if the basic cost C0 for traveling in the virtual blocking area S is selected to be the same as or larger than the maximum value Cm, traveling in the blocking area in a planned manner is not permitted. As shown in FIG. 7D, when the basic cost C0 of the virtual blocking area S is set smaller than the maximum value Cm, it is possible to travel in the blocking area as planned. This is necessary, for example, if the robot is sandwiched between obstacles, or if there is only a limited space between the obstacle and the virtual boundary B to reach the area behind the obstacle. In the case of a "hard" virtual wall, all movement within the virtual occlusion region S is assigned a maximum cost and cannot move within the occlusion region behind the hard virtual wall.

  In a further embodiment of the present invention, after inspection indicates that the robot 100 is located in the virtual blocking area S, the robot 100 stops. The user is notified of this error and is delegated to the user whether to stop the robot at this point until the user can move the robot to another location or until the robot leaves the blocking area S. You. The user can indicate or suggest a route to exit the blocking area S (eg, using the HMI 200). Therefore, the user can directly (remotely) control the robot or specify, for example, a point on the route or a rough direction, and based on this, the robot automatically runs out of the virtual cutoff area S. For example, a virtual boundary B that is controlled so that the robot leaves the blocking area S beyond it can be set. This is useful in the case of areas that can cross and leave different virtual boundaries. For example, a current map can be displayed to the user for this purpose. In addition, for example, the robot has a camera whose images are transmitted to the human-machine interface 200, and the user can point a safe route from the virtual occlusion region based on these images.

  If there is no such possibility that the robot accidentally enters the virtual blocking area S (the robot seeks help) and leaves the blocking area S, the robot stops (emergency stop) to avoid undesired movements for the user. And wait for user intervention. The same is true if the robot cannot automatically move freely or if it stops moving. For example, a robot can be inadvertently locked in by a room user by closing a room door while the robot is performing a task, which causes the robot to return to a base station after the task is complete. You may not be able to return. Other examples are when the robot gets entangled in cables on the floor, when one of the robot's actuators, such as a rotating brush, is blocked, when the robot is pinched between two obstacles, and tries to move further If the danger of falling off the edge is imminent, sensors that are important for the function of the robot do not send data due to contamination, for example, or send only limited data, or other security hazards. There are situations.

  It is common to set the state of the robot to a special mode, such as "emergency stop", to distinguish it from a normal interruption or stop of a task that a user may want. The internal robot state "Emergency stop" means that all actuators (especially working unit 160 and drive unit 170) are stopped and can only be restarted by user (eg, manual) intervention. The user's intervention in this case is, for example, sending a command (eg, using the HMI 200) on how the robot exits this situation. In some cases, manual intervention by the user may be required, such as cleaning the sensor or releasing a blocked actuator.

  The HMI 200 (or other external device 300) can check the status of the robot via the communication unit 140 and thereby notify the user of the problem. Further, the robot can emit audible and / or visual (emergency) signals during an "emergency stop" condition, so that the user can easily find and release the robot.

  However, the autonomous mobile robot 100 continuously transmits signals, which may cause a problem that the battery runs out rapidly while the user is not at home. By the time the user arrives, the battery may be depleted and the robot may turn off and lose signal. Furthermore, neighbors can be disturbed by continuous acoustic signals. The user can be at home, but may not have the time to tackle robot problems. In this case as well, the continuously transmitted signal interferes.

  Therefore, it is appropriate to send an emergency signal only when the user is interested in the device. Thus, the status of the robot can be interrogated via the external device 300 (eg, HMI 200) and if the robot has the aforementioned "emergency stop" status, acoustic and / or optical signals can be transmitted. For example, the status of the robot can be confirmed via an application on a smartphone or tablet PC. In particular, the acquisition of robot status information can be performed automatically at the start of the program. Alternatively, a menu item can be included in the application, and the status information of the robot can be called by calling the menu item. Further, the robot may be configured to send a push message to the HMI 200 via the server 502.

  For example, when the robot recognizes a problem and sets the status to "emergency stop", an emergency signal is transmitted for a predetermined time so that a nearby user can assist the robot. For example, if no help is received for 5 minutes, the robot is switched to a power saving mode until the status of the robot 100 is polled via the external device 300 (eg, all sensors and actuators except the communication unit 140 are switched off). Turn off).

  The user can easily carry a smartphone or tablet PC, and can control the robot from all over the world (eg, via the Internet). However, when the user is not at home in the inquiry about the state of the robot 100, the transmission of the emergency signal by the robot is unnecessary. Thus, for example, the determination as to whether an emergency signal is transmitted takes into account the location of the device for which status is queried, and thus the location of the user. For example, the emergency signal is transmitted only when the position of the device requesting the status is within or near the robot use area. The robot 100 may determine the position of the external device (for example, the HMI 200) based on different data. When the robot transmits an inquiry to, for example, an external device, the external device transmits a response message indicating whether the external device is in the robot usage area. The external device can be configured to locate using a GPS sensor. Also, the inferred (approximate) location of the external device can be indicated by the SSID (Service Set Identifier) of the WLAN to which the external device is logged in. Instead of sending a query, the robot can be configured to independently detect whether an external device is nearby. For example, the robot 100 can determine whether itself and an external device are logged in to the same WLAN. In that case, the robot assumes that an external device (and user) is nearby and is sending an emergency signal. In the example described here, the emergency signal is a signal that is generated directly by the robot itself and that can be perceived (eg, optical or audible) directly (without the assistance of technical equipment) by the user.

  For example, a portable external device can determine its location and notify the robot. This is done, for example, with satellite-based global positioning systems such as GPS, information from mobile networks, or WLAN information. In particular, the direct reachability of the HMI 200 via the local WLAN to which the robot is connected is very good indication that the user is at home.

  The robot can determine whether the user is at home by determining whether the status request from the device is transmitted from a local network such as Wi-Fi at home or communicated via the Internet. Communication connections over the Internet are typically made via a cloud service (see server 502 in FIG. 1) and are therefore clearly distinguishable from local connections. For example, in the case of a status request via the local network, the robot can issue an emergency signal, but in the case of a request via the Internet, this is not performed.

  Furthermore, the presence of the user can be detected using other sensors. For example, a microphone attached to the robot picks up ambient noise, from which it can be inferred whether the user is at home or in and out of the house. Many other external sensors and devices have information about the presence and absence of the user and may share it with the robot. For example, an electronic door lock and / or an alarm system connected thereto transmits information to the robot when a user activates or deactivates the electronic door lock.

B: virtual boundary H: obstacle M: measurement point S: virtual cutoff area Sa, Sb: divided area T: moving trajectory V: force vector W: area 100, 100B: autonomous mobile robot 110: base station 120: sensor unit 121 ... floor sensor 140 ... communication unit 145 ... communication connection 150 ... control unit 151 ... control software module 152 ... navigation module 155 ... processor 156 ... memory 156 ... nonvolatile memory 160 ... working unit 170 ... drive unit 190 ... projector 200 ... human machine Interface 201 Touch screen 300 External device 500 Internet 501 Access point 502 Server

Claims (68)

A method of controlling an autonomous mobile robot configured to uniquely navigate within a robot usage area using a sensor and a map,
Detecting an obstacle based on the measurement data obtained from the sensor, and determining the position of the detected obstacle;
Controlling the robot to avoid collision with the detected obstacle;
Has,
The map may include map data indicating at least one virtual obstruction region, and the at least one virtual obstruction region may similarly consider an actually detected obstacle when controlling the robot. A method characterized by the following.   The robot determines its own unique position, calculates a relative position of the virtual cutoff region with the robot based on the own unique position and the map, and the virtual cutoff region is actually detected. 2. The method according to claim 1, wherein the robot is processed by the robot in the same manner as an obstacle that has been lost. Saving the determined position of the detected obstacle on a map;
Determining the position of the robot by the robot;
Using a route planning algorithm to plan a route to a destination around an obstacle stored in the map, wherein the virtual blocking area is treated as an obstacle stored in the map; The method according to claim 1 or 2, further comprising:   4. The method according to claim 1, wherein the position of the blocking area is stored as a relative position to a landmark registered on the map. 5.   Here, the virtual blocking area is defined by a boundary line that the robot must not cross, and / or the virtual blocking area is defined by an area that the robot must not travel. Item 5. The method according to any one of Items 4 to 6. A method for controlling an autonomous mobile robot configured to uniquely navigate within a robot usage area using sensors and map data,
The map data has at least one virtual boundary line, and the at least one virtual boundary line has a direction that can distinguish a first side and a second side of the at least one virtual boundary line. And
Traversing the boundary line in a first direction coming from the first side of the boundary line while navigating the robot is avoided;
A method wherein the traversal of the boundary in a second direction coming from the second side of the boundary during navigation of the robot is permitted. A virtual boundary line is only temporarily included in the map data in order to distinguish and attach a robot use area processed by the robot during the operation of the robot from the remaining robot use areas,
The method according to claim 6, wherein the orientation of the virtual boundary line is such that the robot can move to an area to be processed but cannot leave the area.   When the robot is on the first side of the boundary, the robot considers the virtual boundary as detected by the sensor of the robot during navigation, as well as the contour of a real obstacle. The method according to claim 6 or 7, wherein an obstacle avoidance algorithm is used. The virtual boundary line is constituted by an open or closed polygon chain whose position is temporarily or permanently stored in the map data,
The virtual boundary line optionally borders one or more contours of one or more real obstacles included in the map data with a virtual occlusion region in the robot usage region. The method according to any one of claims 6 to 8.   10. The method of claim 6, wherein the boundary extends for a defined distance relative to a detected contour of an actual obstacle, and the robot does not approach the obstacle more than a defined distance. A method according to any one of the preceding claims.   The method according to claim 10, wherein the position of the boundary line is stored as a position relative to the actual obstacle. A method for controlling an autonomous mobile robot configured to independently navigate a robot usage area using a sensor and map data, wherein the robot periodically determines its own position in the map. Wherein the map data comprises at least one virtual occlusion region, and wherein the method comprises:
Checking, based on the information stored in the map, whether the robot is at least partially in a virtual occlusion region,
Have. Performing a global self-localization when the robot is moving in the robot usage area, storing a path that the robot has moved,
During or after completion of the global self-localization, a check is performed to determine whether the robot is at least partially within an occluded area; and
As soon as the robot determines that it is in the virtual blocking area, it retreats at least along the stored path until it can safely leave the virtual blocking area, or
The method of claim 12, wherein the robot starts executing a predefined task in the blocking area as soon as it determines that it is already in the virtual blocking area at the start of the self-localization. Performing a global self-localization as the robot moves through the robot usage area, establishing one or more localization hypotheses for the current location of the robot, and for each localization hypothesis, Determining whether is in or near the virtual blocking area;
Controlling the robot such that the robot leaves the blocking area or the distance to the blocking area increases,
13. The method according to claim 12, comprising:   If the inspection reveals that the robot is in a virtual occlusion area, the robot determines, according to a predefinable criterion, whether the robot stops or leaves the occlusion area. The method according to any one of claims 12 to 14.   16. The method of claim 15, wherein the cutoff region is divided into an edge region and a core region, and the predefinable criterion is whether the robot is in the core region or the edge region. Method.   17. The method of claim 15 or claim 16, wherein the robot navigates away from the blocking area by force field analysis after determining to leave the blocking area. A method for controlling an autonomous mobile robot configured to independently navigate a robot usage area using a sensor and an electronic map, wherein the robot determines its own position in the map in a regular manner. , The map data includes at least one virtual occluded area, wherein the method comprises:
Checking whether the blocking area is active or inactive based on pre-definable criteria;
Have
The method wherein the robot considers only the active blocking area and, as a result, does not travel in the active blocking area.   The criterion for whether the occluded area is active is the current time or the elapse of a predefined time interval, the start of which can be defined by a user input on a human-machine interface. 19. The method according to 18.   20. The method according to claim 18 or claim 19, wherein the criterion as to whether the blocking area is active is that the robot performs a specific task.   21. The method according to any one of claims 18 to 20, wherein the criterion of whether the blocking area is active is that another robot performs a specific task.   22. The method according to claim 18, wherein the criterion as to whether the blocking area is active is whether the blocking area is marked as active or inactive by an external device, in particular a human-machine interface. A method according to claim 1.   The robot may leave the blocking area and / or terminate work in the blocking area if the robot previously determined that the inactive blocking area has been activated and the robot is in the blocking area. The method according to any one of claims 18 to 22, characterized in that: A method for controlling an autonomous mobile robot configured to independently navigate in a robot usage area using a sensor and an electronic map, wherein the robot periodically determines its own position in the map. And the map data includes at least one virtual occlusion region, wherein the robot does not automatically travel, the method comprising:
Receiving data representing a virtual blocking area from another robot via a communication connection;
Storing a virtual blocking area on a map of the robot based on the received data;
A method comprising:   The data representing the virtual blocking area is generated by the another robot according to the work currently being performed or already completed, particularly according to the area to be processed or already processed during the work. The method according to claim 24, wherein   25. The method according to claim 24, further comprising the step of deleting a previously stored blocking area in response to a message received from the another robot via the communication connection or after a predetermined time has elapsed. A method according to claim 25. A system having an autonomous mobile robot and an external device,
The robot automatically navigates its environment based on map data,
Detecting a situation where the robot cannot release itself automatically,
It is configured to set the state of the robot according to the detection,
The external device includes:
Configured to send an inquiry to the robot via at least one communication connection to query the status of the robot;
The robot further emits an optical and / or acoustic signal for a predetermined time if the state of the robot at the time of receiving the inquiry from the external device indicates that the robot cannot release itself automatically. The system characterized by being comprised as follows.   The robot determines the position of the external device and emits the optical and / or acoustic signals according to the determined position of the external device, and when the external device is in or near the use area of the robot. 28. The system of claim 27, wherein the system is configured to only transmit the signal.   29. The system of claim 27 or claim 28, wherein the system is configured to detect the presence of a user and transmit a signal only when a user is present. A method for controlling an autonomous mobile robot configured to independently navigate in a robot usage area using a sensor and an electronic map, wherein the robot periodically determines its own position in the map. And the map data can include at least three different classification regions, wherein the method comprises:
Determining its position by the robot using the sensor;
Testing that the robot is in any of the at least three different classification regions;
Has,
Automatically navigating to perform a task when the robot is in a first of the at least three different classification areas;
If the robot is in the second of the at least three different classification areas, it automatically navigates but does not perform a task,
The method of claim 3, wherein a third one of the at least three different classification areas is a virtual blocking area where the robot does not automatically travel.   31. The method of claim 30, wherein the robot determines a path as short as possible or as fast as possible to traverse the second area.   When navigating the robot, a cost function is used to plan the path or work process of the robot, and that the cost of moving the second area is higher than the cost of moving the first area. A method according to claim 30 or claim 31, characterized in that:   The robot travels in the second area only when the robot has completed a current task and / or needs to cross the second area to perform a task. A method according to any one of claims 30 to 32. A method of exchanging information between at least two autonomous mobile robots,
Each of the at least two robots is configured to autonomously navigate a robot usage area using sensors and an electronic map, and to automatically create and update the map;
The robots each include a communication module capable of transmitting information to at least one other robot, the method comprising:
Automatically determining the operation of converting the coordinates of the first map of the first robot into the coordinates of the second map of the second robot;
Transmitting position-related information from the first robot to the second robot;
Using the conversion operation to convert the coordinates of the position-related information of the coordinates of the first map into the coordinates of the second map;
Having a method. Automatically determining the conversion operation,
Calculating the conversion operation based on a first attitude stored on the first map and a second attitude stored on a second map of the same navigation feature, such as a base station. 35. The method of claim 34, wherein   36. The method of claim 34 or claim 35, wherein the transform operation includes shifting, rotating, and, optionally, scaling. A method of inputting a virtual blocking area on an electronic map of a robot use area of an autonomous mobile robot,
Accepting user input from a human-machine interface to define the virtual barrier area;
Evaluating the user input, wherein it is checked whether the user input meets at least one predefined criterion;
Determining whether to store the virtual occlusion region on the map and / or in what geometric form based on the evaluation of the user input;
Having a method.   The method of claim 37, wherein the human machine interface displays the map and the user input is based on the displayed map.   39. The method of claim 38, wherein the human-machine interface is a portable device with a touch screen, and wherein the user input is made through the touch screen.   The user input is surface information that marks an area included in the map, and the step of evaluating the user input includes determining a geometric basic shape representing the marked area in the map. The method according to any one of claims 37 to 39, characterized in that: The user input is line information representing a boundary line,
41. The method according to claim 37, wherein the step of evaluating the user input includes the step of determining the cutoff region based on the outline of the obstacle stored on the boundary line and the map. The method according to claim 1.   The robot according to claim 1, wherein the boundary connects the outline of two obstacles or touches the outline of one obstacle at two different places, and the robot use area is divided into two divided areas. 42. The method according to 41.   43. The method of claim 42, wherein the smaller of the two sub-regions is defined as a virtual cut-off region.   43. The method of claim 42, wherein an area of the two divided areas where the robot and / or the base station is not located is defined as a virtual blocking area.   The method of claim 44, wherein if the robot and the base station are in different sub-regions, a warning message is output to a user via a human-machine interface.   The method according to any one of claims 41 to 45, wherein the boundary is a closed polygon chain, and an area closed by the polygon chain is defined as a virtual occlusion area. .   47. The method of claim 37, wherein the step of evaluating the user input is based on at least one of a shape, a size, and a position of the occlusion region defined by the user input. The method described in.   48. The area of the robot use area where the robot can no longer pass because of the position, the size, or the shape of the virtual occlusion area is automatically added to the virtual occlusion area. the method of.   The method of claim 37, wherein evaluating the user input comprises aligning the occluded area defined by the user input with an outline stored on the map of an obstacle, such as a wall. 49. The method according to any one of claims 48.   The method according to any one of claims 37 to 49, wherein the position of the blocking area defined by the user input is stored as a relative position to a landmark registered on the map. . Evaluating the user input includes detecting an obstacle already stored on the map, and determining a distance from the obstacle,
51. The method according to any one of claims 37 to 50, wherein the blocking area is defined by a boundary line extending a predetermined distance from a detected obstacle already stored in the map. Method. The at least one predefined criterion includes a requirement that the robot not automatically save the virtual occlusion region in the map if the requirement is not met;
The user is informed via the human-machine interface that said requirement is not met,
52. The method according to any one of claims 37 to 51, wherein the virtual occlusion region is saved for confirmation only after further user input via a human-machine interface.   The at least one predefined criterion may include at least the following requirements: that the robot can reach a predefined position in the robot usage area, when an obstruction area is considered. 53. The method according to claim 52.   A check is made as to whether the requirements are fulfilled, in which a path is planned to plan a path from the current position of the robot or a predetermined starting position, for example the position of a base station, to a predefined position. The method of claim 53, wherein a planning algorithm is used. The at least one predefined criterion includes:
(1) the robot can reach a base station when the virtual blocking area is considered;
(2) the robot is outside the virtual blocking area;
(3) The area of the robot use area that does not belong to the virtual cut-off area and can be reached without the virtual cut-off area is a condition that the robot can reach even when the virtual cut-off area is considered. 55. The method according to any one of claims 52 to 54, wherein at least one of the requirements is included.   56. The method according to any one of claims 52 to 55, further comprising, if the requirement is not satisfied, checking whether the requirement is satisfied by changing the virtual blocking area.   57. The method of claim 56, wherein changing the virtual occlusion region comprises manipulating at least one of shifting, rotating, and distorting the virtual occlusion region and / or boundaries of the virtual occlusion region. A method for controlling an autonomous mobile robot configured to independently navigate in a robot usage area using a sensor and an electronic map, wherein the robot periodically determines its own position in the map. Wherein the map includes at least one virtual occlusion region that the robot does not travel when navigating;
Detecting a danger area when navigating the robot use area where the function of the robot is at risk or restricted;
Automatically defining a blockage area surrounding the detected danger area;
Saving the blocking area on the map;
A method comprising:   The detection of the danger area is performed during learning running and / or during use, wherein the robot creates a map of the robot use area, and the map is also used during subsequent use of the robot. 59. The method of claim 58, wherein   59. The dangerous area as claimed in claim 58 or claim 58, wherein the dangerous area includes at least one of a falling edge, an obstacle that the robot cannot detect without contact, and an area where the movement of the robot includes a high degree of slip. 60. The method according to item 59. An autonomous mobile robot configured to automatically navigate a robot usage area based on map data,
A projector configured to project information on a floor or an object in the robot use area,
A system having
The system is configured to extract position-related information from the map data together with a related position, and project the position-related information by the projector onto a corresponding position of the floor or an object on the floor. .   The system of claim 61, wherein the projector is located on the autonomous mobile robot or another robot.   63. The system of claim 61 or claim 62, wherein the system is configured to determine information to project based on a current position and / or orientation of the robot.   63. The system of claim 62, wherein the autonomous mobile robot or the another robot is configured to determine a location that includes a direction in which to project the location-related information.   The system according to any one of claims 61 to 64, wherein the position-related information is a virtual blocking area, a virtual boundary line, an area to be cleaned, or an area that has not been cleaned. An autonomous mobile robot,
The robot is configured to automatically navigate a robot use area based on map data,
The robot is configured to receive position-related information from a user via a human-machine interface, determine a robot path based on the information, and move along the robot path.
An autonomous mobile robot, wherein the position-related information is discarded or permanently stored together with the map data according to a further input of a user after or after the robot moves on the robot path.   67. The robot according to claim 66, wherein the position related information represents a surface area, particularly a virtual occlusion area, and the robot path determined based on the information extends along a boundary of the surface area.   The robot path may be along the boundary of the surface area such that the robot runs entirely within the surface area, runs completely outside the surface area, or runs on the boundary. The robot of claim 67 extending.